Software Engineer (Machine Learning)

Human Intuition. Machine Intelligence. Relentless Exploration.

The Role:

Responsibilities:

• Build AI Agents: Design and deploy agent-based architectures to extract clean trading data from highly unstructured sources.
• Deploy LLMs: Orchestrate frontier and/or self-hosted LLMs to ensure high-fidelity data extraction during volatile market events.
• Engineer the Pipeline: Write scalable, production-quality code that safely delivers AI-generated insights into our live trading infrastructure.
• Maintain Excellence: Champion CI/CD, automated testing, and rigorous deployment standards to ensure system resilience.
• Collaborate on Core Logic: Work directly alongside senior quants to weave your AI systems into our foundational trading algorithms.

The Tech Stack:

• Languages: Python is your primary tool for all AI workflows. (Strong backgrounds in other languages like Java are welcome, provided you are also proficient in Python).
• AI & Orchestration: Frontier LLMs and/or self-hosted models, and agent frameworks (e.g., Open Claw).
• Infrastructure: Cloud-native environments and enterprise deployment tools.
• Core Interoperability: Our low-latency trading engines run on C++. While writing C++ is not a requirement, you should be comfortable building pipelines that interface with high-performance backends.

You Bring:

• Experience: 2–5 years of professional software engineering in a production codebase. (Note: Finance experience is entirely optional—we actively welcome top tech talent from outside the industry).
• Education: A Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Technical Chops: Strong command of Python, data flows, and enterprise-level system architecture.
• Applied AI: Meaningful, hands-on experience building, experimenting with, and deploying LLMs and agent-harnessing tools.
• Bonus (C++): Familiarity with C++ is a great plus. While entirely optional, it allows you to interface more seamlessly with our high-performance trading engines.

Ideal Profile:

• High Agency: The AI landscape changes daily. You are self-motivated, eager to learn, and capable of taking ownership of ambiguous problems.
• Critical Thinker: You don't blindly trust AI outputs. You rigorously review data, understand the underlying logic, and refine parameters to handle edge cases.
• Collaborative Builder: You are energized by working face-to-face within a fast-paced team and communicating clearly with quants.
• On-Site Presence: Willingness to work on-site in our Chicago-area (suburban) office, driving impact in person.

We Offer: